A distribution center should be sized from its operational data: use order profiles to plan work areas, trailer activity to size docks, and peak inventory to set storage capacity. Start there before committing to square footage.
Facility projects often start the other way around, with a target square footage and a site, and the operation is then fitted into whatever building results. The data most companies already hold in their warehouse management, transportation and order systems can do much better than that. Used early, that data turns a vague space requirement into a specific building brief.
Start with the order profile, not the square footage
The order profile describes what a distribution center will actually handle, starting with order lines per day and units per order. Count the active stock-keeping units (SKUs) too, then measure how fast each product moves. Those figures decide how much space goes to fast-moving pick faces, how much to reserve pallet storage and how much to packing and staging.
Two operations with the same annual volume can need very different buildings if one ships full pallets to stores and the other ships single items to homes. Consider an illustrative 12,000-unit day: at 600 units per pallet, that is 20 full-pallet movements. A fulfillment center shipping those units in two-unit orders instead has 6,000 orders to pack, before allowing for split shipments.
The United States Census Bureau’s August 18, 2026 release put e-commerce at 17.1 percent of second-quarter retail sales, seasonally adjusted. As of October 2026, Census flags those estimates as awaiting revision, so use your own order history rather than national sales share to size packing space. Planning around peak volume rather than the yearly average matters as well, because a building sized to the average runs short of staging space and dock time in exactly the weeks that matter most.
Turn trailer data into a dock count
Dock doors are one of the clearest places where data should set the design. The basic calculation multiplies the number of trailers expected in the busiest hour by the average time each trailer occupies a door, measured in hours, then adds an allowance for variability. Running that calculation separately for inbound and outbound traffic establishes each side’s demand; freight flow and yard access also affect whether docks belong on one wall or opposite walls.
For an illustrative peak of eight trailers per hour occupying doors for 90 minutes each, the baseline is 8 × 1.5 = 12 occupied doors. An assumed 80 percent planned door utilization raises the test case to 12 ÷ 0.80 = 15 doors, not a universal design target. For staging, the same flow-rate-times-time relationship explained in Georgia Institute of Technology’s Warehouse & Distribution Science gives 60 pallet spaces if 80 pallets per hour spend 45 minutes waiting. Test those assumptions against actual arrival bursts and putaway timestamps before adding aisle space to the layout.
Returns deserve their own line in the model. A returns stream needs receiving doors, inspection space and staging that do not compete with outbound shipments, and handling returned goods well starts with knowing how much volume is coming back. On a pre-engineered steel building, sections of wall can be designed as knock-out panels, so additional dock positions can be added later as the data changes.
Model growth, then let the building follow it
Throughput forecasts are where predictive analytics matters most, and where a building goes wrong if the forecast is ignored. A five-to-ten-year projection of orders, units and SKU count shows how quickly an operation will outgrow a given footprint, and whether it makes more sense to build for today with a planned expansion or to build larger from the start.
Pre-engineered steel suits a phased approach. One end of the building can be framed from the outset to accept future bays, and each added bay can carry more dock doors along the same wall. Construction speed matters here too.
Factory-fabricated framing can shorten on-site erection, but your expansion schedule still needs to account for permits and equipment installation. When the structure can keep pace with the forecast, an operator can commit to the space the data supports today and add capacity as the numbers confirm the growth.
Let storage cube set the clear height and the grid
Once the order profile and growth model are settled, warehouse inventory data sets the storage requirement. Peak inventory on hand, expressed in pallet positions or storage locations and spread across the racking options, shows how many rack levels the operation needs and therefore how much clear height the building should have. More height adds storage without adding footprint, but it also adds levels to reach, heavier loads on the slab and more demanding fire protection, so the right answer comes from the data rather than from the tallest building available.
The structural grid should follow the same numbers. Universal Steel of America’s distribution center buildings, for example, are engineered to the clear height and rack configuration the operation specifies, with clear spans sized to the racking and drive aisles. Where a very deep building needs a line of columns, the bay spacing is set so the columns fall between back-to-back rack rows rather than in working aisles. That alignment only happens if the racking layout exists before the frame is engineered.
Benchmark before you build
An operation’s current performance is the best evidence of what the next building should fix. The Warehousing Education and Research Council (WERC) 2026 DC Measures report tracks 36 operational metrics, including capacity utilization and dock-to-stock cycle time. Those benchmarks give a reference point for whether today’s constraints come from the building or from the process.
Consider two illustrative facilities with 10,000 usable pallet positions and the same 12-hour dock-to-stock time, measured from receipt to stock availability. At 9,500 occupied positions, the first has only 500 positions free; the second, holding 7,000 pallets, has 3,000 free. Neither result proves that more doors are needed. Check whether receipts wait for an available location or for a putaway operator, since workforce analytics and inventory management need to be assessed together.
From data to building brief
Before a distribution center is designed, the data should answer five questions. Record the peak period and assumptions behind each answer so designers can test the same operating case:
- What does the order profile look like at peak, not on average?
- How many inbound, outbound and returns doors does the trailer data support?
- How much storage, and therefore how much clear height, does peak inventory require?
- Where will throughput be in five to ten years, and how will the building grow to meet it?
- Which of today’s constraints come from the building, and which come from the process?
Before approving the distribution facility’s footprint, ask your team to replay its busiest recorded week against the proposed layout. Require the brief to show where pallets wait when doors are occupied, and what measured demand would trigger the next expansion.
